1. Technical Field
The invention relates to completing a Web-based form with information from a user's profile. More particularly, the invention relates to a reverse mapping method and apparatus for form filling.
2. Description of the Prior Art
Form-fill is a technology that is aimed to automate the task of Web form completion with a user's specific profile information. Almost all Web sites today collect some information from their users. This information could be addresses, names, emails, or even credit card information in case of on-line shopping. For a particular user in most of the cases this involves the user entering the same address or credit card information over and over again. This tedious and error prone process for even Internet savvy users could become prohibitively difficult for novices.
Enter the form-filling technology. It is usually implemented on the user's client, e.g. browser, as a piece of software that knows the user's profile data, such as his first name, last name, street address, phone, etc. It also has a mapping between the user's information and the corresponding fields of the Web form to be filled. The form-filling code then takes information from the user's profile and automatically completes the form with the requested information. The user after that could review, i.e. proof read, the form and simply submit it.
The users' profile data is provided by the user upon the initial setup process or sometimes it can be collected on demand, based on the requirements of the current Web form. The most sophisticated part of the process is in creation of the mapping between the form fields and their meaning. This mapping process is presently known to comprise either of a hard-coded mapping and an intelligent mapping. Hard coded mapping is achieved by manually creating links between the field names and their meanings. Intelligent mapping uses a rule-based approach to search for keywords that would help the software to translate the labels and the text around the field.
Hard-Coded Mapping (Site Profiling)
A major issue with this approach is the cost to collect and maintain profile information for an enormously large set of domains. The cost to support even the top 1000 domains could become prohibitively high. It is thought that this approach is impractical to maintain a list of more than 300 supported domains.
Intelligent Form Fill (IFF)
The problem with IFF is that this can be characterized as natural language understanding, and in some cases even image analysis, both of which are known to present extremely difficult technical issues. Efforts over the last several decades in trying to recreate these simple human abilities with software tools have not been particularly successful. Although, the problem to be solved is limited to recognizing of 10-15 profile attributes correctly, the number of different ways in which Web sites can ask for the same information is still very high. Algorithms known today rely upon dictionaries of keywords and patterns to identify the form fields. Yet, the accuracy of such algorithms is just a little above 85%. Every additional percent in accuracy improvement requires significant trial-and-error, fine-tuning, and regression testing. Additionally, localizing these dictionaries and word patterns in other languages would require the same time-consuming trial-and-error technique. This approach is thus considered to be practically inefficient in achieving and maintaining levels higher than 86-87% accuracy. It is also hard and expensive to extend the service to international languages.
It would be advantageous to provide low-cost, high quality form filling, with coverage of a large number of Web sites, and thereby overcome the limitations of the existing site profiling and IFF solutions.